Proposes an agent-based world model for electromagnetic space in 6G with a case study on reinforcement-learning-inspired feature selection for path loss prediction.
Multidimensional Wireless Environment Features Based Zero-Shot Path Loss Prediction,
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ChannelAgent-Empowered Electromagnetic Space World Model: A Case Study on Agent-Driven Channel Generation for 6G AI-Native Air Interface
Proposes an agent-based world model for electromagnetic space in 6G with a case study on reinforcement-learning-inspired feature selection for path loss prediction.